download Prime Hands-On Machine Learning with C#: Build smart, speedy, and reliable data-intensive applications using machine learning –

Explore supervised and unsupervised learning techniques and add smart features to your applicationsKey FeaturesLeverage machine learning techniques to build real world applicationsUse the Accord machine learning framework for reinforcement learningImplement machine learning techniques using Accord, nuML, and EncogBook DescriptionThe necessity for machine learning is everywhere, and most production enterprise applications are written in C using tools such as Visual Studio, SQL Server, and Microsoft Azure Hands On Machine Learning with C uniquely blends together an understanding of various machine learning concepts, techniques of machine learning, and various available machine learning tools through which users can add intelligent featuresThese tools include image and motion detection, Bayes intuition, and deep learning, to C applicationsUsing this book, you will learn to implement supervised and unsupervised learning algorithms and will be better equipped to create excellent predictive models In addition, you will learn both supervised and unsupervised forms of regression, mainly logistic and linear regression, in depth Next, you will use the nuML machine learning framework to learn how to create a simple decision tree In the concluding chapters, you will use the AccordNet machine learning framework to learn sequence recognition of handwritten numbers using dynamic time warping We will also cover advanced concepts such as artificial neural networks, autoencoders, and reinforcement learningBy the end of this book, you will have developed a machine learning mindset and will be able to leverage C tools, techniques, and packages to build smart, predictive, and real world business applicationsWhat you will learnLearn to parameterize a probabilistic problemUse Naive Bayes to visually plot and analyze dataPlot a text based representation of a decision tree using nuMLUse the Accord machine learning framework for associative rule based learningDevelop machine learning algorithms utilizing fuzzy logicExplore support vector machines for image recognitionUnderstand dynamic time warping for sequence recognitionWho this book is forHands On Machine Learning with C is forCdevelopers who work on a range of platforms from and Windows to mobile devices Basic knowledge of statistics is required Table of ContentsMachine Learning BasicsReflectInsight Real Time Monitoring Bayes Intuition Solving the Hit and Run Mystery and Performing Data Analysis Risk versus Reward Reinforcement Learning Navigating the obstacle course with Fuzzy Logic Color Blending Self Organizing Maps and Elastic Neural Networks Facial and Motion Detection Imaging Filters and Motion Area Highlighting with AccordNet Encyclopedias and Neurons Should I Take the Job Decision Trees in Action Deep Belief Networks Using SharpRBM Micro Benchmarking and Activation Functions Intuitive Deep Learning in CNet Quantum Computing The Future I would not recommend this book It might be used as reference or as a starting point for some machine learning methods using c but I don t really think that will be able to learn many things from it and the editing overall quality is low They could put some effort before publishing Maybe just look online for examples on Accord.NET online instead Finally I felt that the second chapter and the last chapter were completely irrelevant to the topic. Apparently text is basically ported from same named book for python, with statement that it is written for python and R References to colors in pictures but all black and white Don t buy this book Because of very sloppy editing, I don t trust anything in it